Int vs. Float for N_k

[choderalab]

Int vs. Float for N_k

[mrshirts]

I'd have to check. I think it's used as both as an indexing limit and as a
constant, and it was simpler to get good behavior assuming it was an int,
so fancy indexing would be sure to work.

If we go to N_tot x K instead of K x K x N, then a lot of the fancy
indexing requirement disappears, though.

On Thu, Sep 12, 2013 at 7:55 PM, kyleabeauchamp [email protected]:

Does it make sense to use float everywhere for N_k as a way to avoid silly
integer arithmetic issues / casting issues? I suppose there is a slight
reduction in resolution when doing this, but I don't think it's
relevant--the resolution of a float64 is 1E-15...

—
Reply to this email directly or view it on GitHubhttps://github.com//issues/23
.

[jchodera]

Can we just recast N_k internally as a numpy.array float32 or float64, thereby allowing the user to pass in whatever (list, array, integers, floats) and have it all work fine internally once it is stored as a class field?

[kyleabeauchamp]

I don't we need to worry about this, seems working fine.